Estimation and Properties of a Time-Varying EGARCH(1,1) in Mean Model
AbstractTime-varying GARCH-M models are commonly employed in econometrics and financial economics. Yet the recursive nature of the conditional variance makes exact likelihood analysis of these models computationally infeasible. This paper outlines the issues and suggests to employ a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a simulated Bayesian solution in only O(T) computational operations, where T is the sample size. Furthermore, the theoretical dynamic properties of a time-varying-parameter EGARCH(1,1)-M are derived. We discuss them and apply the suggested Bayesian estimation to three major stock markets.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Athens University of Economics and Business in its series DEOS Working Papers with number 1228.
Date of creation: 30 Jul 2012
Date of revision:
Dynamic heteroskedasticity; in mean models; time varying parameter; Markov chain Monte Carlo; simulated EM algorithm; Bayesian inference;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-11-03 (All new papers)
- NEP-ECM-2012-11-03 (Econometrics)
- NEP-ETS-2012-11-03 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-39, November.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Sentana, E. & Fiorentini, G., 1997.
"Identification, Estimation and Testing of Conditionally Heteroskedastic Factor Model,"
9709, Centro de Estudios Monetarios Y Financieros-.
- Sentana, Enrique & Fiorentini, Gabriele, 2001. "Identification, estimation and testing of conditionally heteroskedastic factor models," Journal of Econometrics, Elsevier, vol. 102(2), pages 143-164, June.
- Gabriele Fiorentini & Enrique Sentana Iváñez, 1997. "Identification, estimation and testing of conditionally heteroskedastic factor models," Working Papers. Serie AD 1997-22, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
- Antonis Demos, 2002. "Moments and dynamic structure of a time-varying parameter stochastic volatility in mean model," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 345-357, 06.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
- Sangjoon Kim, Neil Shephard & Siddhartha Chib, .
"Stochastic volatility: likelihood inference and comparison with ARCH models,"
W26, revised version of W, Economics Group, Nuffield College, University of Oxford.
- Kim, Sangjoon & Shephard, Neil & Chib, Siddhartha, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 361-93, July.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1996. "Stochastic Volatility: Likelihood Inference And Comparison With Arch Models," Econometrics 9610002, EconWPA.
- Sangjoon Kim & Neil Shephard, 1994. "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers 3., Economics Group, Nuffield College, University of Oxford.
- James M. Poterba & Lawrence H. Summers, 1989.
"Mean Reversion in Stock Prices: Evidence and Implications,"
NBER Working Papers
2343, National Bureau of Economic Research, Inc.
- Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
- Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1995.
"Estimation of Stochastic Volatility Models with Diagnostics,"
95-36, Duke University, Department of Economics.
- Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1997. "Estimation of stochastic volatility models with diagnostics," Journal of Econometrics, Elsevier, vol. 81(1), pages 159-192, November.
- Poirier, Dale J., 1998. "Revising Beliefs In Nonidentified Models," Econometric Theory, Cambridge University Press, vol. 14(04), pages 483-509, August.
- Sentana, Enrique, 1995.
"Quadratic ARCH Models,"
Review of Economic Studies,
Wiley Blackwell, vol. 62(4), pages 639-61, October.
- Vrontos, I D & Dellaportas, P & Politis, D N, 2000. "Full Bayesian Inference for GARCH and EGARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(2), pages 187-98, April.
- Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
- Stelios Arvanitis & Antonis Demos, 2004. "Time Dependence and Moments of a Family of Time-Varying Parameter Garch in Mean Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(1), pages 1-25, 01.
- He, Changli & Ter svirta, Timo & Malmsten, Hans, 2002. "Moment Structure Of A Family Of First-Order Exponential Garch Models," Econometric Theory, Cambridge University Press, vol. 18(04), pages 868-885, August.
- Chib, Siddhartha, 1993. "Bayes regression with autoregressive errors : A Gibbs sampling approach," Journal of Econometrics, Elsevier, vol. 58(3), pages 275-294, August.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekaterini Glynou).
If references are entirely missing, you can add them using this form.